{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# MODELIŲ MOKYMAS IR GERIAUSIŲ PARAMETRŲ PAIEŠKA" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Date | \n", "Title | \n", "Rating | \n", "
---|---|---|---|
6475 | \n", "2017-05-22 | \n", "Very bad.I can't register any of my … | \n", "1.0 | \n", "
6476 | \n", "2017-05-19 | \n", "Functional platform but seriously lacking in c... | \n", "3.0 | \n", "
6477 | \n", "2017-05-18 | \n", "No reservations. | \n", "5.0 | \n", "
6478 | \n", "2017-05-18 | \n", "I HOPE YOU SEE THIS BEFORE You send … | \n", "1.0 | \n", "
6479 | \n", "2017-05-16 | \n", "Coinbase - the rock star crypto app | \n", "4.0 | \n", "
Pipeline(steps=[('scaler', StandardScaler()),\n", " ('poly', PolynomialFeatures(degree=1)),\n", " ('model', Lasso(alpha=10))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
Pipeline(steps=[('scaler', StandardScaler()),\n", " ('poly', PolynomialFeatures(degree=1)),\n", " ('model', Lasso(alpha=10))])
StandardScaler()
PolynomialFeatures(degree=1)
Lasso(alpha=10)
Pipeline(steps=[('scaler', StandardScaler()),\n", " ('poly', PolynomialFeatures(degree=1)),\n", " ('model', Lasso(alpha=10, random_state=0))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
Pipeline(steps=[('scaler', StandardScaler()),\n", " ('poly', PolynomialFeatures(degree=1)),\n", " ('model', Lasso(alpha=10, random_state=0))])
StandardScaler()
PolynomialFeatures(degree=1)
Lasso(alpha=10, random_state=0)